Nested Named Entity Recognition
44 papers with code • 6 benchmarks • 11 datasets
Nested named entity recognition is a subtask of information extraction that seeks to locate and classify nested named entities (i.e., hierarchically structured entities) mentioned in unstructured text (Source: Adapted from Wikipedia).
Benchmarks
These leaderboards are used to track progress in Nested Named Entity Recognition
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Datasets
GENIA
ACE 2005
ACE 2004
NNE
GUM
Chilean Waiting List
The QUAERO French Medical Corpus
Latest papers
A Unified Generative Framework for Various NER Subtasks
yhcc/BARTNER
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ACL 2021
To that end, we propose to formulate the NER subtasks as an entity span sequence generation task, which can be solved by a unified sequence-to-sequence (Seq2Seq) framework.
A Sequence-to-Set Network for Nested Named Entity Recognition
We utilize a non-autoregressive decoder to predict the final set of entities in one pass, in which we are able to capture dependencies between entities.
Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition
tricktreat/locate-and-label
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ACL 2021
Although these methods have the innate ability to handle nested NER, they suffer from high computational cost, ignorance of boundary information, under-utilization of the spans that partially match with entities, and difficulties in long entity recognition.
An End-to-end Model for Entity-level Relation Extraction using Multi-instance Learning
We present a joint model for entity-level relation extraction from documents.
Structured Prediction as Translation between Augmented Natural Languages
amazon-research/tanl
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ICLR 2021
We propose a new framework, Translation between Augmented Natural Languages (TANL), to solve many structured prediction language tasks including joint entity and relation extraction, nested named entity recognition, relation classification, semantic role labeling, event extraction, coreference resolution, and dialogue state tracking.
Nested Named Entity Recognition with Partially-Observed TreeCRFs
FranxYao/Partially-Observed-TreeCRFs
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With the TreeCRF we achieve a uniform way to jointly model the observed and the latent nodes.
A Boundary Regression Model for Nested Named Entity Recognition
wuyuefei3/BR
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Then, a regression operation is introduced to regress boundaries of NEs in a sentence.
Pyramid: A Layered Model for Nested Named Entity Recognition
LorrinWWW/Pyramid
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ACL 2020
Its hidden state at layer l represents an l-gram in the input text, which is labeled only if its corresponding text region represents a complete entity mention.
Named Entity Recognition as Dependency Parsing
juntaoy/biaffine-ner
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ACL 2020
Named Entity Recognition (NER) is a fundamental task in Natural Language Processing, concerned with identifying spans of text expressing references to entities.
Bipartite Flat-Graph Network for Nested Named Entity Recognition
In this paper, we propose a novel bipartite flat-graph network (BiFlaG) for nested named entity recognition (NER), which contains two subgraph modules: a flat NER module for outermost entities and a graph module for all the entities located in inner layers.
